A simple AI agent built without LangChain or AutoGPT
An ecommerce AI agent can be built with the raw and , without LangChain, AutoGPT, or a large framework. The agent answers real customer questions about product stock, order status, and return policy. Its core design is a loop.
The model receives the conversation, then either answers directly or asks to use a tool. When it asks for a tool, the code runs that tool, adds the result back into the conversation, and calls the model again. The developer does not write if/else for each kind of question.
The model chooses which tool to use, which is the main difference between this agent and a basic chatbot. Seen this way, many are wrapping a loop, a tool lookup, and a step that feeds tool results back to the model.
Key points
- The agent uses the and instead of LangChain or AutoGPT.
- It handles ecommerce questions about stock, orders, and returns.
- The main pattern is a loop that calls the model, runs requested tools, and sends tool results back.
- The model chooses the tool, so the developer does not hardcode routing with if/else rules.
- This simple structure can make token flow and cost easier to inspect.